Improved Empirical Mode Decomposition Using Optimal Recursive Averaging Noise Estimation for Speech Enhancement

Bouchair, Asma; Selouani, Sid‐Ahmed; Amrouche, Abderrahmane; Yakoub, Mohammed Sidi

doi:10.1007/s00034-021-01767-w

Cited by 11 publications

(4 citation statements)

References 39 publications

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“…Various signal processing techniques enhance the detection capabilities of ultrasonic NDT applications, where signals are often mixed with noise. The ultrasonic signals should be denoised, which is feasible using short-time Fourier transform, wavelet transform, improved wavelet transforms, adaptive filtering, and empirical mode decomposition (EMD) [46][47][48][49][50][51][52]. Each technique has its strengths and weaknesses, which are considered when selecting the appropriate method for the given application.…”

Section: 𝑍 = 𝐶mentioning

confidence: 99%

Ultrasonic Pulse-Echo Signals for Quantitative Assessment of Reinforced Concrete Anomalies

Zatar,

Chen,

Nghiem

et al. 2024

Applied Sciences

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This paper presents a study to accurately evaluate defects in concrete decks using ultrasonic pulse-echo signals. A reinforced concrete deck with void defects was designed and evaluated for validation, and a commercial ultrasonic pulse-echo (UPE) device was used to obtain the 2D images of the void defect inside the deck. The UPE image is based on the ultrasonic shear-wave test method and an extended synthetic aperture focusing technique (SAFT). To enhance the accuracy of the defect location in the SAFT imaging, the recorded A-scan data from UPE was analyzed using an advanced denoising approach and defect echo peak extraction, which are based on empirical modal decomposition, Hurst exponent characterization, and Hilbert envelope estimation. The results demonstrated that the location and depth of the void defect in the deck can be accurately assessed by using the developed approach. The new method provides quantitative information of the anomalies inside the deck, which can be used to calibrate the qualitative images of UPC devices with the SAFT.

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Section: 𝑍 = 𝐶mentioning

confidence: 99%

Ultrasonic Pulse-Echo Signals for Quantitative Assessment of Reinforced Concrete Anomalies

Zatar,

Chen,

Nghiem

et al. 2024

Applied Sciences

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“…36 Specially, unsupervised methods based on statistical model can obtain clean signal without excessive constraints of noise information, and it has the advantage of offering a mathematical interpretation to better understand the physical interaction between noise and target signal. 37 The unsupervised method is mainly divided into filter noise reduction and adaptive signal decomposition. Generally, filter noise reduction can weaken the influence of noise and obtain relatively clean signal.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Fault feature recognition of centrifugal compressor with cracked blade based on SNR estimation and adaptive stochastic resonance

Song

et al. 2022

Structural Health Monitoring

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The centrifugal compressor is widely used in modern industry, and the blades are prone to crack due to complex loads and working conditions. Owing to the fault features caused by initial blade cracks are week and easily interfered by strong noise, it is difficult to recognize accurately by traditional methods. In this study, the SNR estimation and adaptive stochastic resonance (SEASR) method is proposed for fault feature recognition of centrifugal compressor with cracked blade. Based on the relationship between SNR and stochastic resonance (SR) parameters, the subtract noise by empirical mode decomposition (SNEMD) method is established with second-order and fourth-order moment (M2M4), hence solving the problem of adaptive SR. The effectiveness of SEASR is tested and analyzed by simulation signals and experimental data. The results demonstrate that the proposed method can accurately recognize fault features of cracked blades and compound faults, where the output SNR is superior to that of the previous methods. It is a new method to realize fault diagnosis for centrifugal compressor with cracked blade and other rotating machinery.

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“…The Hilbert transform has been used in signal processing to map an actual signal into an analytical signal with a complex envelope to obtain specific signal features [27][28]. The Hilbert transform converts a given signal into an analytical signal with a complex envelope, which facilitates the evaluation of the signal envelope and the determination of the TOF of the defect echo signal.…”

Section: Introductionmentioning

confidence: 99%

Ultrasonic Pulse Echo Signals for Detection and Advanced Assessment of Reinforced Concrete Anomalies

Zatar,

Nghiem,

Chen

et al. 2024

Preprint

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This paper presents a study to accurately evaluate defects in reinforced concrete decks using ultrasonic pulse-echo signals. Two validation specimens were designed and tested where reinforced concrete deck slab specimens included planned voids and defects. A commercial Ultrasonic Pulse-Echo (UPE) device obtains 2-D images of the void/defect locations of the reinforced concrete deck. The UPE is based on the ultrasonic shear-wave test method using dry-point-contact transmitting and receiving transducers and employing a synthetic aperture focusing technique. The authors analyzed the recorded UPE A-scan data to enhance the accuracy of estimating the defects' locations using the synthetic aperture focusing technique imaging method. The analysis benefitted from an advanced denoising approach and defect echo peak extraction based on empirical modal decomposition, Hurst exponent characterization, and Hilbert envelope estimation. While output from conventional UPC devices can only provide qualitative results, the new method provides quantitative information on the anomalies inside the reinforced concrete deck. The developed approach accurately assists with assessing the location and depth of the voids/defects in the reinforced concrete deck slabs.

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Improved Empirical Mode Decomposition Using Optimal Recursive Averaging Noise Estimation for Speech Enhancement

Cited by 11 publications

References 39 publications

Ultrasonic Pulse-Echo Signals for Quantitative Assessment of Reinforced Concrete Anomalies

Ultrasonic Pulse-Echo Signals for Quantitative Assessment of Reinforced Concrete Anomalies

Fault feature recognition of centrifugal compressor with cracked blade based on SNR estimation and adaptive stochastic resonance

Ultrasonic Pulse Echo Signals for Detection and Advanced Assessment of Reinforced Concrete Anomalies

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